To date the most successful system built on SC2 is AlphaStar [1]} which achieved grandmaster level, beating expert human players in all three races (Protoss, Zerg, and Terran) online; though it has been defeated by a human, it is ranked over 99.8% of human players. AlphaStar uses a complex combination of machine learning methods; after being initialized using supervised learning from replays of human players, it trains using a population-based reinforcement learning process in which basic agents compete against each other in simulated StarCraft tournament ladder.
Basic macro and micro strategies are acquired from supervised learning on replays, and new strategies emerge during the tournament process which is carefully managed to avoid extincting valuable strategies.
The underlying neural representation includes both a transformer and deep LSTM core, but it is difficult to draw conclusions about their relative contributions.
